no code implementations • NeurIPS 2023 • Kaiwen Wang, Kevin Zhou, Runzhe Wu, Nathan Kallus, Wen Sun
In online RL, we propose a DistRL algorithm that constructs confidence sets using maximum likelihood estimation.
1 code implementation • 26 Apr 2023 • Shitong Shao, Xiaohan Yuan, Zhen Huang, Ziming Qiu, Shuai Wang, Kevin Zhou
Based on this insight, we propose an approach called DiffuseExpand for expanding datasets for 2D medical image segmentation using DPM, which first samples a variety of masks from Gaussian noise to ensure the diversity, and then synthesizes images to ensure the alignment of images and masks.
no code implementations • 12 Jun 2022 • Alexander Wang, Jerry Sun, Kaitlyn Chen, Kevin Zhou, Edward Li Gu, Chenxin Fang
The outbreak of the infectious and fatal disease COVID-19 has revealed that pandemics assail public health in two waves: first, from the contagion itself and second, from plagues of suspicion and stigma.
no code implementations • IJCNLP 2019 • Shengli Sun, Qingfeng Sun, Kevin Zhou, Tengchao Lv
Most of the current effective methods for text classification tasks are based on large-scale labeled data and a great number of parameters, but when the supervised training data are few and difficult to be collected, these models are not available.
no code implementations • 12 Mar 2018 • Sebastian Guendel, Sasa Grbic, Bogdan Georgescu, Kevin Zhou, Ludwig Ritschl, Andreas Meier, Dorin Comaniciu
To foster future research we demonstrate the limitations of the current benchmarking setup and provide new reference patient-wise splits for the used data sets.
no code implementations • 23 Jan 2018 • Qiangui Huang, Kevin Zhou, Suya You, Ulrich Neumann
Specifically, we introduce a "try-and-learn" algorithm to train pruning agents that remove unnecessary CNN filters in a data-driven way.
no code implementations • 22 Nov 2016 • Qiangui Huang, Weiyue Wang, Kevin Zhou, Suya You, Ulrich Neumann
A novel neural network architecture is built for scene labeling tasks where one of the variants of the new RNN unit, Gated Recurrent Unit with Explicit Long-range Conditioning (GRU-ELC), is used to model multi scale contextual dependencies in images.